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104
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ALT
1999
Springer
15 years 6 months ago
On the Uniform Learnability of Approximations to Non-Recursive Functions
Abstract. Blum and Blum (1975) showed that a class B of suitable recursive approximations to the halting problem is reliably EX-learnable. These investigations are carried on by sh...
Frank Stephan, Thomas Zeugmann
ICPR
2010
IEEE
15 years 5 months ago
Pattern Recognition Using Functions of Multiple Instances
The Functions of Multiple Instances (FUMI) method for learning a target prototype from data points that are functions of target and non-target prototypes is introduced. In this pa...
Alina Zare, Paul Gader
ICML
1997
IEEE
16 years 3 months ago
Robot Learning From Demonstration
The goal of robot learning from demonstration is to have a robot learn from watching a demonstration of the task to be performed. In our approach to learning from demonstration th...
Christopher G. Atkeson, Stefan Schaal
CVPR
2009
IEEE
16 years 9 months ago
Contextual Classification with Functional Max-Margin Markov Networks
We address the problem of label assignment in computer vision: given a novel 3-D or 2-D scene, we wish to assign a unique label to every site (voxel, pixel, superpixel, etc.). To...
Daniel Munoz, James A. Bagnell, Martial Hebert, Ni...
125
Voted
GECCO
2006
Springer
161views Optimization» more  GECCO 2006»
15 years 6 months ago
The LEM3 implementation of learnable evolution model and its testing on complex function optimization problems
1 Learnable Evolution Model (LEM) is a form of non-Darwinian evolutionary computation that employs machine learning to guide evolutionary processes. Its main novelty are new type o...
Janusz Wojtusiak, Ryszard S. Michalski